The recent innovative developments have mobilized the marketing efforts of global firms to spark the excitement of digital natives (i.e., Generation Z) with real-time and narrative content [1
]. The possession of distinct beliefs, preferences, and values is engraved in almost every generational cohort which eventually forms different behaviors. These evolving dynamics have led marketers on diverse marketing strategies, as a generic marketing mantra would not be impactful for all generations [3
]. Each generation witnesses its unique technological evolution, one generational cohort could prefer the experience of brick-and-mortar where they can touch and feel the products, while another might prefer the convenience of an online retailing store [4
]. Bashir et al., [4
] suggested that each generation has its own way of shopping, time allocation for it, and selection of brick-and-mortar or online store and that brands must adapt to it accordingly. Chu and Kim [6
] explained that while recognizing the generational differences, brands may change their hedonic/utilitarian use of digital platforms and tools, the data sources they employ, the influence of these platforms on a purchase, and different payment options. The upcoming generation of consumers that marketers need to focus on is Generation Z. Generation Z or “Digital X” is the generational cohort of consumers born between 1995 and the late 2000s [7
]. Generation Z is the first generation to grow up with technology from their early childhood years, there they are more sophisticated in terms of connectivity and information as compared to any prior generation ever [8
]. They are relatively intense users of digital platforms and tools, concerning the number of hours spent and the number of platforms they use as well [9
Narrative or storytelling ads are one example of such ads that tend to generate stronger emotional responses and consumer engagement [10
]. Recent studies on narrative advertising found that story ads are more probable to trigger emotions in viewers, also facial coding has shown that there are more chances that viewers will give expressions while watching a narrative format ad [11
]. Generation Z use more digital channels as compared to their predecessors and their attention is divided between various devices and they prefer quick solutions as they have unlimited information access [13
]. Thus, advertising to Generation Z is different from other generations. They like the brands and products in which they can see their reflection, and prefer realistic and relatable content. Narrative advertising can make consumers imagine themselves experiencing the given product or service [14
]. Henceforth, narrative ads must be investigated in the case of Generation Z as they are an upcoming larger market segment. More and more brands are using narrative advertising to trigger emotional responses in their audience and given the Gen Z online traits and habits, the narrative advertisement could be useful to capture their attention [15
]. The effect of both eWOM and narrative advertisements simultaneously on purchase intentions needs to be measured as both constructs have different conceptions and themes. Through the mediation effects of persuasion knowledge, it would be interesting to determine whether eWOM or narrative advertisement has a more powerful effect on purchase intentions.
Contextually, Pakistan is one of Asia’s rapidly growing e-commerce markets [18
]. As of July 2020, the Pakistan telecommunication authority (PTA) states that there are 81 million 3G and 4G users in Pakistan [19
]. Moreover, there are 83 million broadband users in the country. Meanwhile, the overall cellular subscribers in Pakistan are 167 million. According to Hootsuite [20
], there are 76.38 million internet users in Pakistan. As of January 2020, internet penetration in Pakistan has exceeded 35%. Furthermore, there are almost 37 million social media users in Pakistan. In the case of social media users, Pakistan has a 35% yearly growth as compared to a 21% global average. Moreover, as the numbers of consumers using digital media continue to increase, brands have also followed the trend and almost every major brand in Pakistan has a social media presence. Henceforth, due to the aforementioned factors, the investigation of such a study in the Pakistani context is pertinent.
] employed only Facebook respondents to investigate the electronic word of mouth (eWOM) effect on electronic product consumers, as the scope of advertising has been widened by social media platforms, more and more marketers are using digital advertising thus the effectiveness of eWOM must also be investigated on other platforms. Khwaja and Zaman [22
] also proposed further investigation should be done using different online users falling into diverse age categories and taking other categories of products other than the smartphone to be examined for future research. This could be extended to examine the eWOM impact on generation Z on multiple digital platforms. Menon et al. [23
] limited their research to Twitter posts on airline companies and suggested extending the work to other industries and social media platforms. Considering the aforementioned factors, it is theorized that since Generation Z grew up with unique values, beliefs, socio-cultural, technological, and economic environment; thus, their buying behaviors are divergent and need to be investigated. The purpose of this paper is to examine how narrative advertisement and electronic word of mouth (eWOM) are affecting the purchase intentions of Generation Z. Furthermore, also to explore how persuasion knowledge mediates between narrative advertisement and purchase intentions.
The study is oriented to determine how persuasion knowledge would be mediating between narrative advertising, electronic word-of-mouth and the purchase intentions of Generation Z. Positivist research philosophy has been deployed using a deductive approach for the determination of causality. Quantitative research using survey techniques were executed for the collection of data. Statistical analysis using structural equation modeling (SEM) techniques was deployed to precisely measure theoretical association among the constructs.
3. Materials and Methods
This research follows a descriptive research design that relates to the projection of participants’ experiences. Descriptive research designs are often used by marketers to investigate the traits and habits of consumers. The research followed a positivist philosophy and deployed a deductive approach. Quantitative research was conducted using a structured questionnaire. The research instrument was designed by ensuring that the validity and reliability of all the adapted scales were in the acceptable range. The research instrument comprised twenty-five items and they were evaluated on a 5-point Likert scale. Five items of narrative advertising were adapted from the study of Burnkant and Unnava [83
], three items of activation of persuasion knowledge were adapted from the study of Rozendaal, et al. [84
], ten items of eWOM were adapted from the study of Zhang and Watts [65
], and five items of purchase intentions were adapted from the study of Duffett [1
]. The unit of analysis for this study were individuals who belong to Generation Z, involved in online buying in Pakistan. A nonprobability convenience sampling technique was used for the collection of data. The respondents of the study were students studying in different universities in Pakistan. The data was collected offline, by visiting the campuses. For the affirmation of established theoretical association, the SEM technique was deployed. Covariance-based SEM (CB-SEM) using AMOS 22.0 was used as it ensured advanced statistical data modeling in the determination of causal relationships among constructs. Examining data normality, exploratory factor analysis, confirmatory factor analysis, constructs reliability, discriminant, and convergent validity [85
], and multicollinearity determination were mandatory before testing hypotheses in CB-SEM [87
]. According to Zaman et al. [92
], a sample size of more than 200 respondents is ample for SEM. Meanwhile, a few researchers have suggested a sample size of more than 250 is sufficient for configuring statistical path modeling [88
]. Hence, the data was collected from 304 respondents.
Most of the respondents were female, 173, with a valid percentage of 56.9%, whereas male respondents were 131, with a valid percentage of 43.1%. As the data was collected from Generation Z respondents, therefore, 90% of the respondents were within the age limits of 18–23 years (90%), while 9.9% of the respondents were under 18 years old. The internet usage frequency of this generation was found to be extensively high. Some 83.6% of respondents used the internet at least once a day, while almost 11% of respondents used the internet at least once in seven days. The internet shopping frequency revealed that around 35% of respondents purchased products once in 30 days, while 26.3% bought products online once in 90 days. Table 1
provides a complete reflection of the respondents’ demographic outcomes.
Multivariate normality was determined, and it revealed that there were no normality concerns in the data. The standard deviations of narrative advertisement (NA), purchase intention of Generation Z (PIGZ), persuasion knowledge (PK), and electronic word-of-mouth (eWOM) were 0.92374, 0.84417, 1.03189, and 0.85724 respectively, which is in the acceptance range of +2 and −2. The skewness values of the constructs NA, PIGZ, PK, and eWOM were found to be 0.166, −0.605, −0.081, and −0.447, respectively, which are also in the acceptable range of +1 and −1. Lastly, kurtosis results of all the constructs were between the acceptable range of +3 and −3. These results notify that there were no normality concerns in the data (see Table 2
Model estimation was done using SEM on AMOS 22.0. Initially, data normality, construct validity, reliability and exploratory factor analysis (EFA) was conducted on SPSS 24.0. After the attainment of positive outcomes of the respective tests, confirmatory factor analysis (CFA) was executed on AMOS. One of the key roles of CFA is a reaffirmation of reliability and validity through composite reliability (CR) and average variance extracted (AVE). CFA outcomes provided in Table 3
manifestly indicate that all the results were in the acceptable range. ρ denotes EFA results, λ presents standardized factor loadings, α illustrates Cronbach’s alpha values, CR presents composite reliability values and AVE presents average variance extracted values. All the EFA (Ρ) values were above 0.4, standardized factor loadings (λ) were above 0.3, α and CR values were above 0.7, and AVE values were also above 0.4 (see Table 3
(see also Appendix A
), Figure 1
The configuration of model fitness is another critical aspect of the measurement model. Incremental fit indices and absolute fit indices are the two further divisions of CFA. Standardized root mean squared residual (SRMR), adjusted goodness of fit index (AGFI), root mean square of approximation (RMSEA), chi-square/degree of freedom (χ2/df), and goodness of fit index (GFI) is determined in an absolute fit index. The values of SRMR and RMSEA were 0.055 and 0.059, respectively, which are in the acceptable range (less than 0.08). The χ2/df result was 2.053, which is also in the acceptable range (1–3). Furthermore, GFI and AGFI values were 0.886 and 0.857, which are also adequate (<0.95). The outcomes of incremental fit indices revealed the TLI, NFI, CFI values to be 0.911, 0.861, and 0.923, which are in the permissible range of less than 0.95 (see Figure 2
The discriminant and multicollinearity validity was estimated in which variance inflation factor (VIF) results were in the acceptable range of 1–5, and maximum shared variance (MSV) outcomes were also in the permissible range of less than 1. Moreover, square correlations in diagonals revealed that there were no validity concerns in the respective model (see Table 4
The established hypotheses were consequently examined in the structural model where direct and indirect paths were examined. The direct paths of the first five hypotheses were quite significant as H1, H2, H3, H4, and H5 had path coefficients (beta values) of 0.329, 0.318, 0.386, 0.255, and 0.248, respectively, with t-values greater than 1.96, indicating acceptance of these hypotheses. The indirect effects of H6 and H7 provided path coefficient results of 0.227 and 0.256, respectively. All the hypotheses had p-values of 0.00 which indicated the phenomenal significance of the hypothesized paths. Moreover, the regression result (R2) value of purchase intention of Generation Z (PIGZ) was 0.39, and of narrative advertising (NA) was 0.35 (see Table 5
). Lastly, the structural equation model fit measures are illustrated in Table 6
, indicating χ2/DF, GFI, IFI, CFI, NFI, TLI, AGFI, RMSEA, and SRMR values to be in the acceptable range.
Purchase intention of Gen. Z, R2 = 0.39, narrative advertising, R2 = 0.35
5. Discussion and Conclusions
The results suggest that when the consumer is presented with a narrative advertisement, then it activates the use of persuasion knowledge, and it positively influences the purchase intention of Generation Z. Prior studies have reflected diverse results about the effect of persuasion knowledge, some researchers found its influence negative, while others showed that activation of persuasion knowledge helped increase brand memory and loyalty. Due to the deterioration in the attention spans of consumers, it remains pertinent to investigate whether narrative advertising has a future or not. As of 2020, the attention span of individuals has been reduced to 0.825 seconds. There is an element of storytelling in narrative advertising, which consequently requires longer advertisements [93
]. Thus, the study oriented to precisely measure whether the size of narrative advertising affects Generation Z as per the theoretical directions provided in the prior studies. The results reveal that Generation Z’s purchase intention is influenced when they are presented with narrative advertising. eWOM also plays a significant role when Gen Z make their purchasing decisions. Similarly, eWOM being an interesting evolving phenomenon remains a critical factor to determine along with narrative advertising. Interestingly, the direct effects of eWOM on purchase intentions were slightly less as compared to the impact of narrative advertising. However, the mediation of persuasion knowledge between eWOM and purchase intentions was found to be strong. The Generation Z cohort is quickly taking over the marketplace, and their particular online habits and traits need different marketing strategies to capture their attention. In this context, the research gives insight into how to create an online marketing strategy that resonates with Generation Z. As digital platforms have empowered the consumers in a way that they can control when and where they can avoid the marketing material to interrupt their entertainment, marketers needs to make advertising entertaining in itself. By employing storylines in advertising, marketers can better target this generation, as narrative advertisements can trigger emotions, eventually leading to capturing their attention. Meanwhile, by using the interactive nature of digital platforms, marketers must participate in a two-way dialogue with their audience. As eWOM plays an important role in the decision making of the consumer, digital presence, and positive image are important to capture the attention of Generation Z consumers. The study is beneficial for the practitioners as it would be providing insights to the marketers that how narrative advertising can boost purchase intentions. Generation Z is reckoned to be a difficult generation to target by the marketers; henceforth, the paper provides directions of how Generation Z can be influenced through narrative advertising and eWOM with the mediation of persuasion knowledge. The study would be beneficial for upcoming entrepreneurs too. While designing their marketing strategies, they can make effective use of the cyclical dynamics of open innovation, i.e., deploying eWOM and narrative advertising simultaneously.
6. Future Research Directions
The research is insightful in understanding narrative advertising and electronic word-of-mouth, and how particularly Generation Z is influenced by these. Yet, certain limitations need to be recognized and thus are presented in this section. Firstly, the research is cross-sectional and it would be more significant to study the same variables in longitudinal research as a better understanding can be achieved through longitudinal research to study the behaviors of individuals. This research also took a generic approach considering the online ads that are being displayed on various digital platforms, the same research could be done under controlled settings. For future studies, the narrative advertising effect could be further examined by using different thought protocols; for instance, how prior brand attitude will affect the narrative advertisement process. Furthermore, antecedents of narrative advertising should be unfolded, and dimensional effect should be determined. The impact of narrative and non-narrative advertisements on the purchase intentions of Generation Z must be explored in future studies. Simultaneously determining the effects of narrative and non-narrative advertisements would provide a concrete holistic picture of the subject matter. In terms of digital interaction, eWOM in generic milieu was considered, while future studies could be conducted in a specific product category, or low and high involvement products and how narrative advertising and eWOM can influence in these settings. Lastly, both the effects of narrative advertisement and eWOM could be studied during an actual marketing campaign.